Triggered responses to real-time electroencephalography

ABSTRACT

A method of processing EEG data. The EEG data for a user is read from a user utilizing one or more EEG input devices worn by the user. The EEG data is characterized utilizing one or more processing devices to generate characterized data. The characterized data is categorized utilizing the processing devices to determine a user activity and status of the user associated with the EEG data. The characterized data is analyzed to generate analyzed data. The characterized data is compared against controlled data for the user stored by the one or more processing devices. A service response is generated for one or more systems in communication with the one or more EEG devices to control one or more of ignition, locks, and operations of the one or more systems.

RELATED APPLICATIONS

I. This Application claims priority to pending U.S. provisional patentapplication Ser. No. 62/291,675 entitled “SECURE MOBILE COMPUTER NETWORKFOR CONTENT TARGETING AND TRIGGERED RESPONSES BASED ON REAL-TIMEELECTROENCEPHALOGRAPHY OR BINUARAL BEATS DATA”, filed Feb. 5, 2016, andU.S. utility patent application Ser. No. 15/145,340 entitled “TRIGGEREDRESPONSES BASED ON REAL-TIME ELECTROENCEPHALOGRAPHY” filed on May 3,2016, the entire contents of which are hereby incorporated by referencein their entirety.

BACKGROUND I. Field of the Disclosure

The illustrative embodiments relate to processing electroencephalography(EEG) signals in real-time. More specifically, but not exclusively, theillustrative embodiments relate to a system and method for processingbrain wave data including EEG data in combination with at least acharacterized and categorized information determined for a user.

II. Description of the Art

In recent years the development and commercialization of devices thatcapture noninvasive EEG data has made possible observing a person'sbrain activity. In some cases, these devices have multiple sensors orprobes that are positioned on or within a person's skull, ears, or otherpositions on the head of the user. As a result, brain wave data may beeffectively captured. Unfortunately, solutions for management,processing, and utilization of biometric brain wave data are verylimited or non-existent. In particular, there is a lack ofstandardization that would enable the effective capturing, processing,and reporting of EEG data.

SUMMARY OF THE DISCLOSURE

One embodiment provides a method of processing EEG data. The EEG datafor a user is read from a user utilizing one or more EEG input devicesworn by the user. The one or more EEG input devices sense EEG data andbiometrics of the user. The EEG data is characterized utilizing one ormore processing devices to generate characterized data. Thecharacterized data is categorized utilizing the processing devices todetermine a user activity and status of the user associated with the EEGdata. The characterized data is analyzed to generate analyzed data. Thecharacterized data is compared against controlled data for the userstored by the one or more processing devices. A service response isgenerated for one or more systems in communication with the one or moreEEG devices to control one or more of ignition, locks, and operations ofthe one or more systems. Another embodiment provides a processing systemincluding a memory storing a set of instructions and a processorexecuting the set of instructions to perform the method described above.

Another embodiment provides a processing system for EEG data. The systemincludes input devices sensing EEG data from a number of users. Theinput devices are worn by the plurality of users and capture the EEGdata from the plurality of users. The system includes a number ofsensors that capture measurements including biometric data of the numberof users, orientation, and speed of the number of users. The systemincludes a processor that characterizes the EEG data received from theplurality of users to generate characterized data, categorizes thecharacterized data utilizing the one or more processing devices todetermine a user activity and status of each of the plurality of usersassociated with the EEG data, analyzes the characterized data togenerate analyzed data, wherein the characterized data is comparedagainst controlled data for the user stored by the one or moreprocessing devices, and generates a service response for one or moresystems in communication with the one or more EEG devices to control oneor more of ignition, locks, and operations of the one or more systems inresponse to the generated data and the biometrics.

Another embodiment provides a system, device, and method of processingEEG data. The EEG data for a user is received at a server from one ormore EEG input devices.

The EEG data from the user is characterized utilizing the server togenerate the characterized data. The characterized data is categorizedutilizing the server. The characterized data is analyzed to generateanalyzed data. The analysis includes at least comparing the analyzeddata against control data. A service response is generated utilizing theserver to process the analyzed data. Another embodiment provides aprocessing system including a memory storing a set of instructions and aprocessor executing the set of instructions to perform the methoddescribed above.

Another embodiment provides a processing system for EEG data. Theprocessing system includes a number of input devices that receive EEGdata from a plurality of users. The processing system further includes acharacterization server that characterizes and categorize the EEG datareceived from the number of users to generate characterized data. Theprocessing system further includes an analysis server that analyzes thecharacterized data by comparing the characterized data against controldata to generate analyzed data. The processing system further includes atrigger server that generates a number of service response for each ofthe number of users in response to the analyzed data. The trigger servercommunicates the number of service responses to devices associated witheach of the number of users or input devices.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrated embodiments of the present invention are described in detailbelow with reference to the attached drawing figures, which areincorporated by reference herein, and where:

FIG. 1 is a pictorial representation of a processing system for EEG datain accordance with an illustrative embodiment;

FIG. 2 is a pictorial representation of a server system for processingthe EEG data of FIG. 1 in accordance with an illustrative embodiment;

FIG. 3 is a block diagram of a processing system in accordance with anillustrative embodiment;

FIG. 4 is a flowchart of a process for processing EEG data in accordancewith an illustrative embodiment; and

FIG. 5 is a pictorial representation of a computing system in accordancewith an illustrative embodiment.

DETAILED DESCRIPTION OF THE DISCLOSURE

The illustrative embodiments provide systems, devices, platforms, andmethods for processing brain wave data including embodiments that useEEG data in combination with a user profile, mental state,characterizing information (e.g., age, sex, ethnicity, age, mentalstate, etc.), and categorization information. One embodiment providesfor securely obtaining EEG brain wave data from any number of devices,systems, equipment, networks, components or peripherals. In oneembodiment, the brain wave data may be characterized and categorized.For example, the brain wave data sets may then be systematicallyanalyzed within a variety of specialized fields-of-use, such as videogaming, military, medical, and so forth. The analysis of the brain wavedata sets may be securely performed utilizing through any number ofnetworks (e.g., cellular, local area network (LAN), wide area network(WAN), Ethernet network, etc.) or native processing platforms. Theprocessing system utilized to process and analyze the brain wave datamay perform comparisons, normative analysis, and application specificservice responses. The processing of the brain wave data may beperformed automatically utilizing a single device (e.g., server,wireless device, personal computing device, etc.) or through acombination of systems and devices (e.g., cloud network, server farms,etc.).

The illustrative embodiments leverage the power of EEG reading devicesand increases in mobile and networked processing power to moreeffectively analyze EEG data. As a result, the EEG data may be moreeffectively captured and utilized for numerous fields-of-use. Forexample, the EEG data may be processed and analyzed utilizing a standardformat that may be adjusted or customized for any number of industries,fields-of-use, or groups of users. The illustrative processing platformsmay utilize any number of cloud networks, mobile systems, databasemanagement, data portal interfaces, and acquiring technologies. Securitystandards, protocols, and signals, including encryption may be utilizedto secure the EEG data before and after processing to protect userconfidentiality, privacy, as well as legal rights, such as thoseprovided by HIPAA. The illustrative embodiments provide systems andnetworks that are adapted to provide sufficient security and datatransfer to enable it EEG data to be securely captured and processed.

The processed brain wave data is utilized to generate and assembleunique service responses or other actions. In one embodiment, the uniqueservice responses may include 1) adaptive targeted content, 2) computercode, or 3) active trigger commands. The adaptive targeted content mayinclude video, audio, html, digital images, mobile application content,video game content, 3D printing data, instructions, algorithms, and/orany other content that may be communicated or produced by a computer orwireless device. Computer code may include scripts, database data orinstructions, home automation commands, computing, financial, ormathematical algorithms that include java, JavaScript, xml, html, and/orother programming languages. The active trigger commands may includeinstructions, commands, navigation, controls or signals used toactivate, invoke, or control action of devices, machines, systems,equipment, components, digital environments, or physical environments.The service responses may be utilized to adjust stimuli, conditions,parameters, data, or information presented to the user or made to theenvironment of the user. As a result, the brain waves of the user aswell as the associated EEG data may be adjusted in real-time to meetdesired levels, thresholds, outputs, results, conditions, or effects.

The perception and processing of brain wave data may be performed forspecific fields-of-use, categories, endeavors, systems, or facilitiesincluding, but not limited to, medical, human performance, military,construction, crisis management, correctional facilities, behavioralhealthcare, scientific study, travel, security operations, and anynumber of other fields. The illustrative embodiments providecustomizable data characterizations, modalities, and services responsesthat may be based on analysis of below average, normative, andexceptional brain wave data sets pertaining to each category orfield-of-use. The illustrative embodiments may provision automatedservice responses that may help the user (e.g., perform necessary ordesired tasks, relax, concentrate, etc.).

The illustrative embodiments provide for the effective management,processing, and utilization of brain wave data and production ofsystematic homogenous and usable standardization for the production oftargeted digital data and content. The illustrative embodiments providefor the creation of real-world responses, triggers, and actionable datasets derived from the EEG data. Standardized and ubiquitous systems,methods, and devices for ingesting, processing, reporting, and acting onthe EEG data may provide very valuable in numerous fields-of-use.

FIG. 1 is a pictorial representation of a processing system 100 for EEGdata 101 in accordance with an illustrative embodiment. The processingsystem 100 may represent a platform, environment, or system forprocessing EEG data 101. The processing system 100 may include a network102. In one embodiment, the network 102 may receive and process the EEGdata 101 from the input devices 103.

The EEG data 101 may represent data captured by any of the input devices103 for any number of users. The EEG data 101, represents the recordedelectrical activity of a user's brain, such as voltage fluctuationsresulting from ionic current within the neurons of the brain. The EEGdata 101 from each of the input devices 103 will be distinct and uniqueas the the users utilizing the input devices. For example, the patterns,frequencies, amplitudes, thresholds, and sensor readings for the EEGdata 101 may vary significantly. The brain is made up of approximately100 billion nerve cells. The activity of these neurons in the braintissue creates active current sources that cause local electricalpotential to fluctuate with a great deal of variability. As noted, eachbrain is unique both physically and functionally. The folding of thecortex of the human brain is highly individualized such that thecharacteristics of the external surface of the brain (as folded) affectthe electrical potentials within the brain. The processing platform 100may be utilized to process the EEG data 101 as a way of treatingdiseases, processing the EEG data 101, and generating various stimuli.In one embodiment, a single user may wear or utilize a number ofdifferent input devices.

The network 102 may include network components 104. The networkcomponents 104 may represent any number of servers, databases, switches,routers, bridges, modems, mainframes, hardwired connections, wirelessconnections, private networks (e.g., fiber optic, Ethernet, LANs, etc.),public networks, or other devices, systems, equipment, or components. Inone embodiment, the network 102 may represent a distinct processingplatform for processing the EEG data 101 from the input devices 103. TheEEG data 101 may be received in any number of formats. In oneembodiment, the EEG data 101 is received as raw brain wave data that isprocessed within the network 102. In another embodiment, the EEG data101 may be processed or minimally processed by the input devices 103.For example, the EEG data 101 may be packetized, digitized, or otherwiseformatted for communication to the network 102 for processing andanalysis.

In one embodiment, the input devices 103 may include input devices106-112. The input devices 103 may represent any number of noninvasiveor invasive devices. For example, the input devices 103 may includesensors, probes, pins, or electrodes that are positioned against,adjacent, or within the head, ear canal, or scalp of the user. The inputdevices 103 may be configured to both receive and generate signals forreceiving the EEG data 101 as well as modifying, controlling, orenhancing the EEG data 101. For example, the input devices 103 mayutilize optogenetics whereby neurons within the brain are controlledwith light. Using optogenetics, a light-sensitive molecule may beinserted into the cell surface of a neuron. The light-sensitive moleculemay then allow an outside user to trigger or inhibit the firing of theneuron by pulsing a specific frequency of light. Common noninvasiveinput devices 103 may include headsets, deep ear probes, graphing patch,sunglasses, wearables, helmets, hearables, electronic stickers,electronic headgear, or so forth.

The input devices 103 may also generate or communicate audio, video,optical, electrical, magnetic, or other signals, waves, media,communications, or stimuli that may be communicated directly orindirectly to the user (e.g., brain, ears, eyes, skin, etc.). As aresult, the input devices 103 may represent EEG devices that may bothread EEG data 101 as well as generate stimuli that affects or changesthe EEG data 101. The input devices 103 may be utilized to shape thebrain waves, response, mental status, physical status, or condition ofassociated users for health reasons, enhanced performance, experiments,or so forth.

In one embodiment, the input devices 103 may reliably capture the EEGdata 101 without invasive probing or biological insertions that requirethe penetration of skin, brain tissue, ear canal, or other portion ofthe exterior of the skull. The input devices 103 may represent braincomputer interfaces (BCI) that capture the EEG data 101 for recording,processing, utilization, or display to one or more users. The processedEEG data 101 may also be utilized by one or more applications executedby devices, such as the input devices 103, a wireless device 114, or acomputing device 116. Any number of neuroprosthetics may be utilized asthe input devices 103 or in their stead. In other embodiments the inputdevices 103 may represent more invasive probes, electrodes, surgicalimplants, or so forth that may be utilized for health or diagnosticreasons.

The processing platform 100 may act as a communication pathway between abrain of a user (i.e., central nervous system), and one or more externalcomputing devices. In one embodiment, the processing platform 100 maydigitally interface the user for the purpose of augmenting or repairinghuman cognition. For example, the EEG data 101 may be analyzed toaddress epilepsy, sleep disorders, encephalopathies, brain death,tumors, stroke, focal brain disorder, and so forth. Delta, Theta, Alpha,Beta, and Gamma waves of the EEG data 101 may represent key aspects ofthe EEG measurements utilized to determine the state-of-mind, mentalstress, focus, or relaxation of users.

The EEG data 101 may be received directly from the input devices 103 orthrough one or more devices or networks. In one embodiment, the inputdevices 110 and 112 may communicate directly with the network 102 or aprocessing system that analyzes the EEG data 101. For example, anynumber of Bluetooth, Wi-Fi, cellular, or other radio frequencycommunications signals may be utilized to communicate the EEG data 1012and an analyzing device or separate processing system. In anotherembodiment, the input device 106 may communicate the EEG data 101through a wired connection (e.g., packets, Ethernet, serialcommunications, parallel communications, etc.) to the wireless device114 for subsequent communications. The wireless device 114 maycommunicate with the network 102 (e.g., routers, modems, cell towers,transceivers, etc.) utilizing a wireless network connection 118. Thewireless network connection 118 may represent a Wi-Fi, Bluetooth,cellular, or other wireless connection, link, or signal. The inputdevice 112 may be worn positioned substantially within the ear canal ofthe user.

In one embodiment, the processing system 100 may represent aclient/server architecture in which the clients are represented by theinput devices 103 and the servers are represented by the various devicesand components of the network 102. In another embodiment, the wirelessdevice 114, or the computing device 116 may perform the processing ofthe EEG data 101. In the illustrative embodiments, remotely networkeddevices, or local native devices may perform the processing of the EEGdata 101. The brain wave analysis performed by the input devices 103 maybe utilized to enhance performance or behavior of the user in aparticular field-of-use or as a way of treating neurological andphysical diseases, conditions, or issues. For example, music, audio,optical signals, electrical pulses of various frequencies may beutilized to treat a user in-situ, at a clinic, in a hospital, or soforth. In one embodiment, signal patterns may be utilized to affect theusers.

The processing platform 100 may analyze the different types of waves,variables, frequencies, and attributes of the EEG data 101. Someinformation regarding the various brain waves of the EEG data 101 areprovided for purposes of understanding the analysis performed by theprocessing platform 100 as well as a determined or estimated mentalstate of the user.

Delta Waves: Delta is the frequency range up to 4 Hz. Delta waves areoften the highest in amplitude and the slowest waves. Delta waves areoften observed in adults in slow wave sleep. Delta waves are alsoobserved in babies. Delta was may occur focally with subcortical lesionsand in general distribution with diffuse lesions, metabolicencephalopathy hydrocephalus or deep midline lesions. Delta wavesusually occur most prominent frontally in adults (e.g. FIRDA—FrontalIntermittent Rhythmic Delta) and posteriorly in children (e.g.OIRDA—Occipital Intermittent Rhythmic Delta). Theta Waves: Theta is thefrequency range from 4 Hz to 7 Hz. Theta waves are often observed inyoung children. Theta waves may also be observed during drowsiness,meditation, or arousal in older children and adults. Excess theta wavesfor any given person's age represents abnormal activity. Theta waves maybe seen as a disturbance in focal subcortical lesions and may be seen ingeneralized distribution in diffuse disorder, metabolic encephalopathy,deep midline disorders, or some instances of hydrocephalus. The range ofwith theta waves have often been associated with reports of relaxed,meditative, and creative states.

Alpha Waves: Alpha is the frequency range from 7 Hz to 14 Hz. Alphawaves are often referred to as the “posterior basic rhythm” (also calledthe “posterior dominant rhythm” or the “posterior alpha rhythm”), seenin the posterior regions of the head on both sides, higher in amplitudeon the dominant side. Alpha waves may emerge when users close theireyes, with relaxation, and may attenuate with eye opening or mentalexertion. The posterior basic rhythm is actually slower than 8 Hz inyoung children (therefore technically in the theta range). Sensorimotorrhythm is also known as mu rhythm. In addition to the posterior basicrhythm, there are other normal alpha rhythms such as the mu rhythm(alpha activity in the contralateral sensory and motor cortical areas)that emerges when the hands and arms are idle; and the “third rhythm”(alpha activity in the temporal or frontal lobes). Alpha may also beabnormal. For example, an EEG data 101 that has diffuse alpha occurringin coma and is not responsive to external stimuli is referred to as“alpha coma.”

Beta Waves: Beta is the frequency range from 15 Hz to about 30 Hz. Betawaves are commonly seen on both sides in symmetrical distribution andare most evident frontally. Beta activity is closely linked to motorbehavior and is generally attenuated during active movements. Lowamplitude beta waves with multiple and varying frequencies may be oftenassociated with active, busy or anxious thinking, and activeconcentration. Rhythmic beta with a dominant set of frequencies may beassociated with various pathologies and drug effects, especiallybenzodiazepines. Beta waves may be absent or reduced in areas of thebrain with cortical damage. Beta waves are the dominant rhythm inusers/patients who are alert or anxious or who have their eyes open.

Gamma Waves: Gamma is the frequency ranges approximately 30 Hz to 100Hz. Gamma rhythms may represent a binding of different populations ofneurons together into a network for the purpose of carrying out acertain cognitive or motor functions.

Mu waves range from 8 Hz to 13 Hz, and partly overlaps with otherfrequencies. Mu waves reflect the synchronous firing of motor neurons ina rest state. Mu wave suppression is thought to reflect motor mirrorneuron systems because when an action is observed, the patternextinguishes, possibly because of the normal neuronal system and themirror neuron system “go out of sync,” and interfere with each other.

The processing system 100 may perform EEG analysis based on attributesof the users (not shown) of each of the input devices 103. For example,readings may vary based on the age of the user, sex, sleeping or mentalstate, ethnicity, physical attributes, and so forth.

FIG. 2 is a pictorial representation of another communication system 200for processing the EEG data 202 in accordance with an illustrativeembodiment. As shown, the EEG data 202 is captured from a user 203 bythe input device 204. In one embodiment, the EEG data 202 is sent to aprocessing system 206 through a network 208. The network 208 mayrepresent the Internet, a LAN, wireless networks, WANs, or any number orcombination of other private and/or public networks. The EEG data 202may be sent directly or indirectly to the processing system 204. Anynumber of communications connections or mediums (e.g., wireline,wireless, etc.) may be utilized to receive the EEG data 202. The EEGdata 202 may be securely communicated. For example, the security may beat a level suitable for compliance with the Health Insurance Portabilityand Accountability Act of 1996 (HIPAA).

In one embodiment, the EEG data 202 is processed by one or more serverswhich may include a characterization server 210, an analysis server 212,and a trigger server 214 (jointly the “servers 211”). In otherembodiments, the processing system 206 may represent a single server,cloud system, server farm, device, system, or equipment. The servers 211may access one or more databases, such as database 224. The database 224may include control data 226 utilized to further analyze the EEG data202. The EEG data 202 may be processed and analyzed utilizing a numberof customized or standard systems that may perform comparative,normative, and application specific analysis. The analysis performed bythe processing system 206 may be performed automatically in response tothe EEG data 202 being received. As a result, the EEG data 202 may beprocessed in real-time, near real-time, or at a later time based onsaved or otherwise compiled EEG data 202.

The EEG data 202 may be processed by the characterization server 210 togenerate the characterized data 216. The characterized data 216 may beprocessed by the analysis server 212 to generate the analyzed data 218.The analyzed data 220 may be processed by the trigger server 214 togenerate the service response 222. Although FIG. 2 shows only the EEGdata 202 received from the user 203 wearing the input device 204, theEEG data 202 may represent distinct data (e.g., discrete, streaming,etc.) received from any number of users and input devices, such as thoseshown in FIG. 1.

The characterizing server 210 performs characterizing and categorizingof the EEG data 202 to generate the characterized data 216. In oneembodiment, the characterizing server 210 characterizes the EEG data 202utilizing information associated with the user 203 utilizing the inputdevice 204 to generate the EEG data 202. The characterizing server 210may characterize the EEG data 202 to determine age, sex, bodytemperature, blood pressure, perspiration level, pulse rate, mentalstate (e.g., rested, tired, scared, alert, happy, anxious, excited,nervous, etc.), ethnicity, and other information associated with theuser 203. The characterizing server 210 may determine any number ofbiometrics of the user 203 based on the input device 204, wearables,environmental sensors, or electronics associated with the user 203. Forexample, the EEG data 202 may be characterized based on the numeric ageof the user 203 as expressed as a parameter in years, months, and/ordays.

The characterizing server 210 may also categorize the EEG data 202. Thecategorization may determine a specified field-of-use applicable to theuser 203. For example, the categorization may indicate whether the user203 is participating in sports, health or medical treatments, truckdriving, mining, or other activities. The EEG data 202 may also becategorized by the characterizing server 210 to indicate the mental orphysical state of the user 203 at the time the EEG data 202 is createdand captured by the input device 204. Categorization may be importantbecause the state of mind and biofeedback indicated by the EEG data 202may vary based on the activity and state of mind of the user 203. Thestate of the user 203 may indicate whether the user 203 is awake,sleeping, exercising, stressed, relaxed, resting, working, laughing,crying, seizing, or other state associated with a present activity,personality, or affliction of the user 203 at the time the EEG data 202is captured by the input device 204. The characterizing server 210 mayutilize the location, historical activities, designated activities,position, orientation, applications-in-use, or other information anddata to categorize the activity being performed by the user 203.

The characterizing server 210 may also characterize and categorize theEEG data 202 based on the control data 226 or other information and datastored within the database 224. For example, the control data 202 mayinclude activity, employment, medical, user profile, and otherinformation associated with the user 203 or determined for other users.

The analysis server 212 may perform additional analysis and comparisonsof the characterizing data 210. The analysis server 212 may determinewhether the characterized data 216 conforms or does not conform with thecontrol data 226. The analyzed data 218 may represent the results offurther analyzing the characterized data 216. The control data 226 mayrepresent benchmark data, standard values, historical data, expectedresults, patterns, normative ranges, thresholds, or so forth that may bespecific to the user 203 or to users that are most similar to the user203. The control data 226 may be generated utilizing any number ofhistorical data sets associated with the user 203, similar users (e.g.,subsets of users of similar age, ethnicity, health level, etc.), orlarge groups of users. For example, control data 226 that matches thecharacterized data features of the EEG data 202 as processed by thecharacterizing server 210 may be utilized for analysis.

The analyzed data 218 may be utilized by the trigger server 214 togenerate the service response 222. The service response 22 may include aseries of digital and executable commands, content, code instructions toother devices within the communication system 200, and specifiedstimuli. The service response 222 may be sent to the user 203 or thirdparties 230. The third parties 230 may represent any number ofauthorized users, administrators, caregivers, parents, coaches,officers-in-charge, devices, systems, or other individuals, groups,companies, or organizations. The third parties 230 may be set by theuser 203 or an administrator. For example, the user 203 may specifyindividuals, such as parents, coaches, trainers, tracking systems, ormedical professionals that are allowed to receive the queued data aswell as the associated contact information or method (e.g., cell phoneand number, IP address, text message and number, email and emailaddress, phone call and phone number, etc.). In one embodiment, the user203 may specify whether the data may be transmitted as saved, queued, orin real-time. In another embodiment, an administrator, such as a parent,guardian, coach, or medical professional, may specify the devices,individuals, businesses, or organizations included within the thirdparties 230 as well as the associated contact information. In oneembodiment, the service response 222 may include data, control, command,software, or physical responses sent to the user 203, input device 204,or other devices, components, equipment, or users in the environment ofthe user 203.

At any time, the processing system 206 may send the raw EEG data 202,characterized data 216, analyzed data 218, service response, or data,information, or signals at any state of processing within the processingsystem 206, to compatible, excepting, or authorized systems representedby the third parties 230. As a result, the information and datacaptured, characterized and categorized, analyzed, and generated serviceresponses may be checked, verified, authenticated, duplicated, orotherwise monitored.

The service response 222 may be generated based on conformance ornonconformance of the analyzed data 218, with expected results. Theservice response 222 may represent specified service responses fordifferent fields-of-use. The service response 222 may include adaptivetargeted content, computer code, or triggers that may be performed bythe input device 204 or an associated wireless, computing, gaming,entertainment, or control device, system, or component. The serviceresponse 222 may also include any number of reports or alerts associatedwith the EEG data 202 of the user 203.

In one embodiment, the user 203 is a worker in the construction industryand the EEG data 202 applies to the user as she operates heavy machinerywhile wearing the input device 204. The EEG data 202 may be sent througha Wi-Fi network for local processing by the construction company or aconstruction consortium or to an external organization or body withsufficient processing power, such as the processing system 206 toperform the processing and analysis of the EEG data 202. In anotherembodiment, the EEG data 202 may be process by a specialized wirelessdevice in communication with the input device 204. As a result, the EEGdata 202 may be effectively and quickly processed at a construction sitewithout the need for additional networks or processing systems.

In another embodiment, the EEG data 202 is characterized and categorizedby the characterization server 210 to generate the characterized data216. The EEG data 202 may be compared against the control data 226 ofsimilar control subjects, such as females, within the constructionindustry, operating heavy machinery, within a selected age range, andethnicity. The characterized data 216 may be further processed by theanalysis server 212 to determine the fatigue level and mental state ofthe user 203 within the communication system 200. The analyzed data 218is utilized by the trigger server 214 to generate the service response222. The service response 222 may be utilized in an ongoing process tomonitor the user 203. If a determination is made by the processingsystem 206 that the user is physically or mentally fatigued, access tothe worksite, heavy machinery, or so forth may be limited automatically.For example, the user 203 may be required to take a 15-minute to30-minute break. In other examples, specific thresholds regardingphysical or mental state may automatically lock the user 203 out ofcritical systems for a preset time period (e.g., 30 minutes, 12 hours,etc.).

In another example, the service response 222 may include an alert thatis sent to a supervisor or managerial staff indicating the conformanceor nonconformance of the EEG data 202 with a desired result (i.e., idealexpected results from the control data 226). The supervisor may thenmake a decision regarding whether the user 203 may continue to operatethe heavy machinery. The service response 222 may also be sent directlyor indirectly to one or more systems or devices.

In another embodiment, the user is an inmate or patient in a correctionsor treatment facility. The EEG data 202 may be captured by a sourceprobe (e.g., input device 204). The EEG data 202 may be characterizedand categorized by the characterization server 210. The EEG data 202 maybe categorized as it relates to a 48-year-old Caucasian male in thecorrections facility. The characterized data 216 may then be comparedagainst the control data 226 to determine whether the aggression leveland mental state of the user 203 indicates that he may be a danger tohimself and/or others. The analyzed data 218 may be then communicatedfrom the analysis serer 212 to the trigger server 214. In oneembodiment, the service response 222 generated may limit the usersaccess to specific portions of the facility as well as to otherindividuals within the facility (e.g., employees, other inmates orpatients, etc.). The trigger server 214 may generate a trigger responsethat implements an action plan for the facility. In one embodiment, thetrigger server 214 may automatically activate monitoring systems, suchas a surveillance system, user biometrics, enhanced security, and othersystems. In a home monitoring environment, the trigger response mayactivate a warning system to indicate that the user 203 is not allowedto leave his residence. The trigger response may also engage anaudio/entertainment system as a way of calming the user 203 withspecified music, entertainment, or other media. The service response 222may represent any number of preemptive activities and actions that mayhelp, protect, and calm the user 203.

In another embodiment, the user 203 may represent a soldier orcontractor for the armed forces. The EEG data 202 may be analyzed todetermine the mental readiness, concentration levels, calmness, fatiguelevels, and mental state of the user 203. In one embodiment, the inputdevice 204 may be built into a helmet, user monitor, heads-up display(HUD), communications headset, or other equipment, devices, orsub-system associated with the user 203. For example, the input device204 may be connected to an aircraft, Humvee, tank battleship, marinevehicle, machinery, or other land, air, or water vehicles utilized as atool or transport vessel by the user 203. The EEG data 202 may beutilized to determine whether the user 203 is ready and able to utilizethe vehicle as well as the associated equipment, devices, features, andfunctions, and systems. The service response 222 may delivery fullyprocessed data to compatible systems that may allow or deny the user 203access to vehicles, systems, equipment, devices, scenarios, operations,jobs, tasks, and so forth as described herein. The service response 222may automatically grant or deny access in real-time or may requireapproval from a third party (e.g., commander, administrator, supervisor,etc.) before granting or denying access. The process may be implementedfor training, day-to-day activities, combat, or other operations andprocedures the user 203 may participate in. For example, in response todetermining the user 203 is under extreme duress, monitoring activitiesfor the group associated with the user 203 may be implemented. Inanother example, weapons systems may be taken off-line in response todetermining the user 203 is no longer in control of his emotions.

In one embodiment, the service response 222 may be compiled for a numberof users and sent to a person-in-charge to make a decision, such as theideal soldiers for an assignment, job, or task based on their currentphysical, mental, and emotional state as determined by EEG readings froma number of input devices. For example, conformance or nonconformance ofthe users' data (e.g., EEG data 202) with the control data 226 may beutilized to generate the analyzed data 218 and subsequently the serviceresponse 222. The service response 222 may implement display ofapplicable information to the user 203 as well as other users proximateor associated with the user 203. Any number of other actions may also beimplemented.

In another embodiment, the communications system 200 may be applicableto the transportation industry. For example, the user 203 may representa driver, pilot, captain, or operator of a vehicle or system, such asaircraft, busses, cruise ships, trucks, and other passenger, cargo, andmass transit vehicles and systems. The EEG data 202 processed by theprocessing system 206 may be similarly utilized to generate the serviceresponse 222 to control access to job sites, cockpits, control panels,command bridges, driver's seats, navigation systems, drive systems, orso forth. In one embodiment, the service response 222 may send an alertindicating that the user 203 needs to be relieved, actively engaged, orstimulated because of fatigue, intoxication, or mental readiness.

In other embodiments, the communications system 200 may be applicable tothe physical therapy, pharmaceutical, and behavioral health industries.The EEG data 202 may be processed by the processing system 206 for thepurposes of generating the service response 222 to perform diagnosis,real-time interventions, therapy, treatment, assessments, monitoring,prescribed medicine responses, effectiveness of treatment analysis, orother applications. For example, the types of brain waves present in theEEG data 202 may indicate the status of the user.

In other embodiments, the communication system 200 may be applicable tosports (e.g., professional, collegiate, recreational, personal, etc.) orhuman performance industries. The EEG data 202 may be processed by theprocessing system 206 for the purposes of determining calmness, mentaldistress, mental trauma, physical condition and so forth. The serviceresponse 222 may be generated to perform real-time analysis of sportsperformance, concussion analysis, implement commands, execute controlsystems, initiate or enhance performance and biometric monitoring, andother applications.

In one embodiment, the database 224 may store, queue, copy, or archivethe EEG data 202 and other data within the processing system 206 as itis processed to generate the service response 222. The database 224 maystore the service response 222 so that it may be searched, sorted, andaccessed on-demand. For example, the EEG data 202 and the serviceresponses 222 may be searched from any number of computing orcommunications devices with authorized access to the processing system206 and the associated data. For example, the processing platform 206may execute a database management system to access and control the rawand processed data.

FIG. 3 is a block diagram of a processing system 300 in accordance withan illustrative embodiment. The processing system 300 is one embodimentof a computing or communications device configured to process EEG datareceived from any number of devices. For example, the processing system300 may represent a server. The processing system 300 may process theEEG data locally, through a direct connection, or through one or morenetworks. In one embodiment, the processing system 300 may be integratedwith an EEG reading device, such as a headset, virtual reality device,helmet, or so forth.

In one embodiment, the processing system 300 may include a processor, amemory, sensors 306, a transceiver 308, a characterization module 310, acategorization module 312, an analysis module 314, and a response module316.

In one embodiment, the processor 302 is the logic that controls theoperation and functionality of the processing system 300. The processor302 may include circuitry, chips, and other digital logic. The processor302 may also include programs, scripts, and instructions that may beimplemented to operate the logic engine 302. The processor 302 mayrepresent hardware, software, firmware, or any combination thereof. Inone embodiment, the processor 302 may include one or more processors.The processor 302 may also represent an application specific integratedcircuit (ASIC) or field programmable gate array (FPGA). The 302 mayutilize sensor measurements, user input, user preferences and settings,conditions, factors, and environmental conditions to process the EEGdata from the user. The components of the processing system 300 mayfunction separately or together to process the EEG data. For example,processing may be divided between multiple devices (e.g.,characterization server, analysis server, trigger server, web server,etc.) in communication with the processing system 300 to increase thespeed of processing and to load balance any processes being performed.

In one embodiment, the processor 302 may perform any number ofmathematical, signal analysis, and statistical analysis, processing, andcomputation to process and compare the EEG data against control data.The processor 302 may utilize time and other sensor measurements ascausal forces to enhance mathematical functions, analysis, andprocessing utilized to perform the processes, steps, and determinationsherein described.

The processor 302 is configured to perform all or a substantial portionof the processing needed for the illustrative embodiments. In oneembodiment, the processor 302 may perform characterization,categorization, analysis (e.g., comparative analysis), responsegeneration, and communications and alerts. In one embodiment, theprocessor 302 is a logic engine including circuitry or logic enabled tocontrol execution of a set of instructions. The processor 302 may be oneor more microprocessors, digital signal processors, application-specificintegrated circuits (ASIC), central processing units, or other devicessuitable for controlling an electronic device, such as the processingsystem 300, including one or more hardware and software elements,executing software, instructions, programs, and applications, convertingand processing signals and information, and performing other relatedtasks.

The memory 304 is a hardware element, device, or recording mediaconfigured to store data or instructions for subsequent retrieval oraccess at a later time. The memory 304 may represent static or dynamicmemory. The memory 304 may include a hard disk, random access memory,cache, removable media drive, mass storage, or configuration suitable asstorage for data, instructions, and information. In one embodiment, thememory 304 and the processor 302 may be integrated. The memory 304 mayuse any type of volatile or non-volatile storage techniques and mediums.The memory 304 may store information related to a number of applicableusers, processing system 300, input device, user-specific EEG data,historical EEG data, thresholds, associated alerts, indicators, andwarnings, and so forth. In one embodiment, the memory 304 may store,display, or communicate instructions, programs, drivers, or an operatingsystem for controlling interconnected systems, interfaces, EEG devices,or other systems, equipment, devices or components. The memory 304 mayalso store biometric readings or user input required for specified data,functions, or features, authentication settings and preferences,thresholds, conditions, signal or processing activity, historicalinformation, proximity data, and so forth.

The transceiver 308 is a component comprising both a transmitter andreceiver which may be combined and share common circuitry on a singlehousing. The transceiver 308 may communicate utilizing Bluetooth, Wi-Fi,ZigBee, Ant+, near field communications, wireless USB, infrared, mobilebody area networks, ultra-wideband communications, cellular (e.g., 3G,4G, 5G, PCS, GSM, etc.), infrared, or other suitable radio frequencystandards, networks, protocols, or communications. For example, thetransceiver 308 may coordinate communications and actions between theprocessing system 300 and a number of input devices utilizing Wi-Ficommunications. The transceiver 316 may also be a hybrid transceiverthat supports a number of different communications. For example, thetransceiver 316 may communicate with a wireless EEG headset (not shown)utilizing Bluetooth communications and with a cloud network and remoteparties utilizing Ethernet communications.

The sensors 306 may include EEG sensors, probes, or detectors forreading EEG signals or the currents, potentials, or phase changesassociated with the neuroelectrical changes within the brain of theuser. In other embodiments, the sensors 306 may also include inertialsensors, pulse oximeters, accelerometers, gyroscopes, impact/forcedetectors, thermometers, photo detectors, barometers, altimeters, globalpositioning systems, speedometers, miniature cameras, microphones (e.g.,ear-bone, external, etc.), and other similar instruments for readinginformation, data, and other biometrics associated with the user or theenvironment of the user. The sensors 306 may also be utilized todetermine the biometric, activity, location, and speed measurements ofthe user. In one embodiment, the sensors 306 may store data that may beshared with other components, users, and devices. The sensor data mayalso be utilized to perform automated actions, implement processes, orso forth. For example, the processing system 300 may generate responsesto the EKG readings that may include wave forms (e.g., bianaural beats,monaural tones, isochronic tones, etc.) for trigging brain frequencychanges. As a result, the processing system 300 may adjust the user'sbehavior, response, or reaction to various stimuli.

The processing system 300 may include characterization module 310,categorization module 312, analysis module 314, and response module 316.The various modules may represent hardware, software, firmware, or acombination thereof. The characterization module 310 may be utilized toperform characterization as herein described, including withoutlimitation determining information associated with the user (e.g., age,sex, ethnicity, etc.), physical status (e.g., pulse, temperature, etc.),and mental/emotional status (e.g., calm, agitated, scared, excited,etc.). The characterization module 310 may receive feedback from thesensors 306 as well as input devices, such as EEG devices which mayinclude user interfaces. Thus, the characterization module 310 mayautomatically determine categorization details or may receive data andinformation from the user, databases, communications systems, or otherdevices, systems, or parties.

The categorization module 312 may be utilized to determinecategorization as herein described, including without limitationdetermining an activity associated with the user. The categorizationmodule 312 may determine the activity based on the user's position,location, orientation, speed, calendar, altitude, activity level, or soforth. The characterization module 310 and the categorization module 312may communicate with medical record databases, employment records,emergency databases, or so forth.

The analysis module 314 analyzes data that has been characterized andcategorized. The analysis module 314 may store control data that may becompared against the incoming EEG data stream. The analysis module 314may analyze the characterized and categorized data to determinecompliance, noncompliance, or deviations with expected or desired EEGdata. The control data may be specific to the user or may be generatedbased on other groups, groups of individuals, or so forth.

The response module 316 may utilize the analyzed data to determine aresponse based on the EEG data. The response module 316 may utilize theanalyzed data to generate alerts, responses, dynamic feedback for theuser, commands, sets of instructions, indicators, flags, or otherresponses. The communications from the response module 316 may be sentto the user, designated parties/devices, or any number of third parties.

In one embodiment, all or portions of the processing system may includenon-transitory computer-readable media. The non-transitorycomputer-readable media may include all computer-readable media exceptfor a transitory propagating signal within the processing system 300.For example, binaural beats data may be sent to the user to subliminallyalter the brain waves of the user to a desired state or conditionutilizing audio communicated to the user.

The components of the processing system 300 may be electricallyconnected utilizing any number of wires, contact points, leads, busses,wireless interfaces, or so forth. In addition, the processing system 300may include any number of computing and communications components,devices or elements which may include busses, batteries, motherboards,circuits, chips, sensors, ports, interfaces (e.g., user, card, port,hardware, etc.), cards, converters, adapters, connections, transceivers,displays, antennas, and other similar components.

FIG. 4 is a flowchart of a process for processing EEG data in accordancewith an illustrative embodiment. The process of FIG. 4 may beimplemented by one or more systems or devices, such as a server as isreferenced herein. In one embodiment, the process of FIG. 4 may beimplemented by a server and database configured to communicate with anumber of EEG capture devices directly or indirectly. FIG. 4 may also beimplemented by a series or group of servers (e.g., characterization andcategorization, analysis, trigger, etc.) configured to receive EEG datafrom any number of sources. The process of FIG. 4 may alternatively beperformed by a wireless device that receives the EEG data. The steps ofFIG. 4 may be performed jointly, separately, or in any number ofcombinations of orders (e.g., sequentially, concurrently,simultaneously, etc.).

The process of FIG. 4 may begin by receiving EEG data from one or moreinput devices (step 402). As previously noted, the EEG data may becaptured by any number of input/output devices, such as helmets,headsets, sunglasses, electronic headgear, virtual reality device,earpieces, probes, transponders, or so forth. The EEG data may bereceived for a single user or for multiple users utilizing the inputdevices. The server may be configured to process a single stream of EEGdata or multiple streams of data simultaneously. The EEG data may bereceived directly by the server or through any number of intermediarydevices or networks. In one embodiment, the EEG data may be packaged orpacketized by the input devices for communication. The EEG data may alsobe encoded, encrypted, or otherwise formatted for efficientcommunication as well as security. In other embodiments, the EEG datamay be sent in a raw format as read by the input devices (e.g., rawanalogic or digital EEG readings, etc.).

Next, the server characterizes and categorizes the EEG data (step 404).Characterization may include age, sex, pulse rate, ethnicity, and otherfactors that may affect the EEG readings performed by the input devices.Characterization may also include determining the state of mind ormental state of the user. Categorization may include determining anactivity the user is engaged in, such as football player, train driver,truck driver, airplane pilot, crane operator, surgeon, and any number ofactivities, industries, or professions the user is engaged in. In oneembodiment, one or more external databases or devices may be utilized todetermine information and data that is utilized to perform thecharacterization and categorization. For example, the server may accessa database, application, or interface of employee information, medicalrecords, user entered information, and other applicable information thatis automatically determined, captured over time, or user generated.

Next, the server analyzes the characterized data against control data(step 406). During step 406, the characterized and categorized data iscompared against control data that may include standardized, baseline,normative, threshold, performance based, or other data and information.The server may determine whether the EEG data conforms or does notconform with the control data during step 406 to generate analyzed data.In one embodiment, the server may determine whether changes to theenvironment, equipment, parameters, circumstances, or environment thataffect the user may need to be made. For example, the user,administrator, or other party may want the EEG data for the user to beas close as possible to the EEG data.

Next, the server generates service response utilizing the analyzed data(step 408). The service response may represent a response to the user'sEEG data as analyzed by the server. The service response may include anynumber of active or passive responses. For example, a coach,administrator, supervisor, parent, or other interested party may provideinput or feedback (e.g., in-person, audibly, visually, tactilely, etc.)to the user in response to the EEG data. The feedback may be sentthrough the input devices, utilizing associated devices (e.g., vehiclesystems, weapon systems, cell phones, computing devices, etc.), orutilizing devices in the user's environment. The service response may beutilized control one or more actions, provide feedback, preemptively act(e.g., rotate soldiers to prevent post-traumatic stress, change drivers,provide additional stimulus to calm the user, provide positive feedbackto help a scared user, etc.), provide precursor information.

Next, the server communicates the service response to one or moreparties (step 410). The service response may be communicated toindividuals, groups, organizations, systems, devices, equipment,components or so forth. For example, the service response may becommunicated to the user, the input device, or any number of other thirdparties as processed EEG data, warnings, alerts, recommendations, or soforth. In one embodiment, the service response may include digitalcontent, computer code, or one or more trigger commands.

In one embodiment, the service response may include binaural beats.Neurons within the brain generate electric currents and the synchronousaction of the neurons may represent macroscopic oscillations which maybe monitored by the EEG data capture for the user. Such oscillations maybe characterized by frequency, amplitude, and phase. Neural tissuewithin the brain may generate oscillatory activity driven by mechanismswithin individual neurons as well as their interactions. Audio signalsmay be generated by the input devices wherein the jointly processed(e.g., by the inferior colliculus of the midbrain and the superiorolivary complex of the brainstem) to generate electrical impulses of theneural pathways up the midbrain to the thalamus, auditory cortex, andother cortical regions of the brain. Sounds, music, or other signals maybe generated to best precipitate different changes in the neuraloscillations and correlating EEG readings of the user to alter theuser's cognitive and emotional state. This processed may also bereferred to as neuronal entrainment or brain wave entrainment. In oneembodiment, binaural beats, monaural tones, and isochronic tones may beutilized as a triggered response for brain wave entrainment. Eachdifferent type of response may have advantages and disadvantages forspecific brain waves (e.g., Beta, Alpha, Theta, Delta, etc.). In oneembodiment, isochronic tones may be utilized to achieve a desiredresponse in the user.

The illustrative embodiments provide for systems, devices, and methodsfor processing brain wave data into a systematic and homogenous formatfor processing. As a result, the brain wave data, such as EEG data, maybe more effectively processed. In addition, responses may be moreeffectively generated including audio inputs, electrical brain wavestimulation, visual stimulation

The illustrative embodiments may take the form of an entirely hardwareembodiment, an entirely software embodiment (including firmware,resident software, micro-code, etc.) or an embodiment combining softwareand hardware aspects that may all generally be referred to herein as a“circuit,” “module” or “system.” Furthermore, embodiments of theinventive subject matter may take the form of a computer program productembodied in any tangible medium of expression having computer usableprogram code embodied in the medium. The described embodiments may beprovided as a computer program product, or software, that may include amachine-readable medium having stored thereon instructions, which may beused to program a computing system (or other electronic device(s)) toperform a process according to embodiments, whether presently describedor not, since every conceivable variation is not enumerated herein. Amachine readable medium includes any mechanism for storing ortransmitting information in a form (e.g., software, processingapplication) readable by a machine (e.g., a computer). Themachine-readable medium may include, but is not limited to, magneticstorage medium (e.g., floppy diskette); optical storage medium (e.g.,CD-ROM); magneto-optical storage medium; read only memory (ROM); randomaccess memory (RAM); erasable programmable memory (e.g., EPROM andEEPROM); flash memory; or other types of medium suitable for storingelectronic instructions. In addition, embodiments may be embodied in anelectrical, optical, acoustical or other form of propagated signal(e.g., carrier waves, infrared signals, digital signals, etc.), orwireline, wireless, or other communications medium.

Computer program code for carrying out operations of the embodiments maybe written in any combination of one or more programming languages,including an object oriented programming language such as Java,Smalltalk, C++ or the like and conventional procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The program code may execute entirely on a user's computer,partly on the user's computer, as a stand-alone software package, partlyon the user's computer and partly on a remote computer or entirely onthe remote computer or server. In the latter scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN), a personal area network(PAN), or a wide area network (WAN), or the connection may be made to anexternal computer (e.g., through the Internet using an Internet ServiceProvider).

FIG. 5 depicts a computing system 500 in accordance with an illustrativeembodiment. For example, the computing system 500 may represent a serveror processing system, such as the processing system 300 of FIG. 3. Thecomputing system 500 may be utilized to process EEG data by performingcharacterization, categorization, analysis, response generation, and soforth. The computing system 500 includes a processor unit 501 (possiblyincluding multiple processors, multiple cores, multiple nodes, and/orimplementing multi-threading, etc.). The computing system includesmemory 507. The memory 507 may be system memory (e.g., one or more ofcache, SRAM, DRAM, zero capacitor RAM, Twin Transistor RAM, eDRAM, EDORAM, DDR RAM, EEPROM, NRAM, RRAM, SONOS, PRAM, etc.) or any one or moreof the above already described possible realizations of machine-readablemedia. The computing system also includes a bus 503 (e.g., PCI, ISA,PCI-Express, HyperTransport®, InfiniBand®, NuBus, etc.), a networkinterface 505 (e.g., an ATM interface, an Ethernet interface, a FrameRelay interface, SONET interface, wireless interface, etc.), and astorage device(s) 509 (e.g., optical storage, magnetic storage, etc.).The system memory 507 embodies functionality to implement embodimentsdescribed above. The system memory 507 may include one or morefunctionalities that facilitate retrieval of the audio informationassociated with an identifier. Code may be implemented in any of theother devices of the computing system 500. Any one of thesefunctionalities may be partially (or entirely) implemented in hardwareand/or on the processing unit 501. For example, the functionality may beimplemented with an application specific integrated circuit, in logicimplemented in the processing unit 501, in a co-processor on aperipheral device or card, etc. Further, realizations may include feweror additional components not illustrated in FIG. 5 (e.g., video cards,audio cards, additional network interfaces, peripheral devices, etc.).The processor unit 501, the storage device(s) 509, and the networkinterface 505 are coupled to the bus 503. Although illustrated as beingcoupled to the bus 503, the memory 507 may be coupled to the processorunit 501.

The present invention is not to be limited to the particular embodimentsdescribed herein. In particular, the present invention contemplatesnumerous variations in the type of ways in which embodiments of theinvention may be applied to [Insert high-level or more detaileddescription of the invention]. The foregoing description has beenpresented for purposes of illustration and description. It is notintended to be an exhaustive list or limit any of the disclosure to theprecise forms disclosed. It is contemplated that other alternatives orexemplary aspects are considered included in the disclosure. Thedescription is merely examples of embodiments, processes or methods ofthe invention. It is understood that any other modifications,substitutions, and/or additions may be made, which are within theintended spirit and scope of the disclosure. For the foregoing, it canbe seen that the disclosure accomplishes at least all of the intendedobjectives.

The previous detailed description is of a small number of embodimentsfor implementing the invention and is not intended to be limiting inscope. The following claims set forth a number of the embodiments of theinvention disclosed with greater particularity.

What is claimed is:
 1. A method of processing electroencephalography(EEG) data, the method comprising: reading the EEG data from a userutilizing one or more EEG input devices worn by the user, the one ormore EEG input devices sense EEG data and biometrics of the plurality ofusers; communicating the EEG data to one or more processing devices;characterizing the EEG data utilizing the one or more processing devicesto generate characterized data; categorizing the characterized datautilizing the one or more processing devices to determine a useractivity and status of the user associated with the EEG data; analyzingthe characterized data to generate analyzed data, wherein thecharacterized data is compared against controlled data for the userstored by the one or more processing devices; and generating a serviceresponse for one or more systems in communication with the one or moreEEG devices to control one or more of ignition, locks, and operations ofthe one or more systems in response to the generated data and thebiometrics.
 2. The method of claim 1, wherein the one or more inputdevices include at least a helmet or a headset worn by the user.
 3. Themethod of claim 1, wherein the one or more processing devices areintegrated with the one or more EEG input devices.
 4. The method ofclaim 1, wherein the service response includes command codes for the oneor more processing devices.
 5. The method of claim 1, wherein theservice response includes stimuli applied to the user utilizing at leastthe one or more EEG input devices.
 6. The method of claim 1, wherein thecontrol data includes baseline data and historical data for the user. 7.The method of claim 1, wherein the generating a service response furthercomprises: sending one or more alerts to designated users.
 8. The methodof claim 1, further comprising: communicating the service response tothe one or more systems through a transceiver.
 9. The method of claim 1,wherein the EEG data is communicated wirelessly to the one or moreprocessing devices utilizing a transceiver.
 10. The method of claim 1,further comprising: providing a stimulus through the one or more EEGinput devices as part of the service response.
 11. A processing systemfor EEG data comprising: a plurality of input devices sensing EEG datafrom a plurality of users, the plurality of input devices are worn bythe plurality of users and capture the EEG data from the user; aplurality of sensors within each of the plurality of input devicescapture measurements including biometric data of each of the pluralityof users, orientation, location, and speed of the plurality of users; aprocessor characterizes the EEG data received from the plurality ofusers to generate characterized data, categorizes the characterized datautilizing the one or more processing devices to determine a useractivity and status of each of the plurality of users associated withthe EEG data, analyzes the characterized data to generate analyzed data,wherein the characterized data is compared against controlled data forthe user stored by the one or more processing devices, and generates aservice response for one or more systems in communication with the oneor more EEG devices to control one or more of ignition, locks, andoperations of the one or more systems in response to the generated dataand the biometrics.
 12. The processing system of claim 10, wherein eachof the plurality of input devices and the plurality of sensors and theprocessor are included in a helmet or headset.
 13. The processing systemof claim 10, further comprising: a transceiver configured to communicatethe service response to the one or more systems.
 14. The processingsystem of claim 10, wherein the service response includes authorizedcommands for the one or more processing devices.
 15. A processing systemcomprising: one or more EEG input devices worn on a head of a user andcapturing EEG data and biometrics directly utilizing a plurality ofsensors, a memory storing a set of instructions; a processor executingthe set of instructions, wherein the instructions are executed by theprocessor to: characterize the EEG data utilizing the one or moreprocessing devices to generate characterized data, categorize thecharacterized data utilizing the one or more processing devices todetermine a user activity and status of the user associated with the EEGdata, analyze the characterized data to generate analyzed data, whereinthe characterized data is compared against controlled data for the userstored by the one or more processing devices, and generate a serviceresponse for one or more systems in communication with the one or moreEEG devices to control one or more of ignition, locks, and operations ofthe one or more systems in response to the generated data and thebiometrics.
 16. The processing system of claim 15, wherein the set ofinstructions are further executed to determine an activity, orientation,location, and speed of the user utilizing the EEG data and thebiometrics.
 17. The processing system of claim 15, wherein the serviceresponse includes authorized commands for the one or more processingdevices.
 18. The processing system of claim 15, wherein the plurality ofinput devices, the plurality of sensors, the processor, and the memoryare included in a helmet or headset.
 19. The processing system of claim15, wherein the service response is generated based on an activity ofthe user.
 20. The processing system of claim 15, wherein the serviceresponse is one of a plurality of predetermined service responsesincluding at least requiring the user to take a break, activating analert, granting access to the one or more systems, providing a stimulusto the user, and providing instructions to the user.